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<table width="100%" summary="page for Caravan"><tr><td>Caravan</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>The Insurance Company (TIC) Benchmark

</h2>

<h3>Description</h3>

<p>The data contains 5822 real customer records. Each record
consists of 86 variables, containing sociodemographic data (variables
1-43) and product ownership (variables 44-86). The sociodemographic
data is derived from zip codes. All customers living in areas with the
same zip code have the same sociodemographic attributes. Variable 86
(<code>Purchase</code>) indicates whether the customer purchased a caravan
insurance policy. Further information on the individual variables can
be obtained at  http://www.liacs.nl/~putten/library/cc2000/data.html

</p>


<h3>Usage</h3>

<pre>Caravan</pre>


<h3>Format</h3>

<p>A data frame with 5822 observations on 86 variables.
</p>


<h3>Source</h3>

<p>The data was originally supplied by Sentient Machine Research
and was used in the CoIL Challenge 2000.
</p>


<h3>References</h3>

<p>P. van der Putten and M. van Someren (eds) . CoIL Challenge
2000: The Insurance Company Case.  Published by Sentient Machine
Research, Amsterdam. Also a Leiden Institute of Advanced Computer
Science Technical Report 2000-09. June 22, 2000. See
http://www.liacs.nl/~putten/library/cc2000/<br />
P. van der Putten and M. van Someren. A Bias-Variance Analysis of a Real World Learning Problem: The CoIL Challenge 2000. Machine Learning, October 2004, vol. 57, iss. 1-2, pp. 177-195, Kluwer Academic Publishers<br />
James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013)
<em>An Introduction to Statistical Learning with applications in R</em>,
<a href="www.StatLearning.com">www.StatLearning.com</a>,
Springer-Verlag, New York
</p>


<h3>Examples</h3>

<pre>
summary(Caravan)
plot(Caravan$Purchase)
</pre>


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